Abstract

Fine needle deflection is a problem encountered during insertion into a soft tissue. Although an axial rotational insertion is an effective approach for minimizing this problem, needle deflection still depends on the insertion angle with respect to the tissue boundary. Since the human body consists of multilayered tissues of various shapes and mechanical properties, preoperative planning of an optimal path is a key factor for achieving a successful insertion. In this letter, we propose an optimization-based preoperative path planning model that minimizes needle deflection during multilayered tissue insertion. This model can determine the optimal path based on the sum of insertion angles with respect to each tissue boundary that the needle passes through. To increase the accuracy of the model, we incorporated the effect of distances from tissue boundaries and the probability that the deflection is acceptable by incorporating weighting factors into the model. To validate the model, we performed experiments involving four scenarios of two- and three-layered tissues. The results showed that the proposed model is capable of determining the optimal insertion path in all scenarios.

abstract = "Fine needle deflection is a problem encountered during insertion into a soft tissue. Although an axial rotational insertion is an effective approach for minimizing this problem, needle deflection still depends on the insertion angle with respect to the tissue boundary. Since the human body consists of multilayered tissues of various shapes and mechanical properties, preoperative planning of an optimal path is a key factor for achieving a successful insertion. In this letter, we propose an optimization-based preoperative path planning model that minimizes needle deflection during multilayered tissue insertion. This model can determine the optimal path based on the sum of insertion angles with respect to each tissue boundary that the needle passes through. To increase the accuracy of the model, we incorporated the effect of distances from tissue boundaries and the probability that the deflection is acceptable by incorporating weighting factors into the model. To validate the model, we performed experiments involving four scenarios of two- and three-layered tissues. The results showed that the proposed model is capable of determining the optimal insertion path in all scenarios.",

N2 - Fine needle deflection is a problem encountered during insertion into a soft tissue. Although an axial rotational insertion is an effective approach for minimizing this problem, needle deflection still depends on the insertion angle with respect to the tissue boundary. Since the human body consists of multilayered tissues of various shapes and mechanical properties, preoperative planning of an optimal path is a key factor for achieving a successful insertion. In this letter, we propose an optimization-based preoperative path planning model that minimizes needle deflection during multilayered tissue insertion. This model can determine the optimal path based on the sum of insertion angles with respect to each tissue boundary that the needle passes through. To increase the accuracy of the model, we incorporated the effect of distances from tissue boundaries and the probability that the deflection is acceptable by incorporating weighting factors into the model. To validate the model, we performed experiments involving four scenarios of two- and three-layered tissues. The results showed that the proposed model is capable of determining the optimal insertion path in all scenarios.

AB - Fine needle deflection is a problem encountered during insertion into a soft tissue. Although an axial rotational insertion is an effective approach for minimizing this problem, needle deflection still depends on the insertion angle with respect to the tissue boundary. Since the human body consists of multilayered tissues of various shapes and mechanical properties, preoperative planning of an optimal path is a key factor for achieving a successful insertion. In this letter, we propose an optimization-based preoperative path planning model that minimizes needle deflection during multilayered tissue insertion. This model can determine the optimal path based on the sum of insertion angles with respect to each tissue boundary that the needle passes through. To increase the accuracy of the model, we incorporated the effect of distances from tissue boundaries and the probability that the deflection is acceptable by incorporating weighting factors into the model. To validate the model, we performed experiments involving four scenarios of two- and three-layered tissues. The results showed that the proposed model is capable of determining the optimal insertion path in all scenarios.